I recently returned from a conference in Chicago called CampIT where the predominant question on every IT professional's mind there was about digital transformation and what it really means to me and my business.
The revolutions in technology are numerous as of late. Cloud, Data, AI, Mobile, Analytics to name just a few and add to those ranks Digital Transformation. But what is it, and what does it really mean? If we use the expression 'to transform digitally' literally, we end up with a definition that is as vague as it is meaningless. What does it mean to become more digital? Does that mean less paper, less people, less reality and more virtual reality?
As it turns out, I myself am not very good at interpreting the generic categorical expressions of new technologies. Cloud was a meaningless term to me until I saw (and experienced) how one could easily deploy applications and technologies using hosted infrastructures like AWS and Azure. Big Data was an equally meaningless term to me. I mean large amounts of data, sure, but it was a meaningless expression until again I saw (and experienced) how creating Hive applications against large data sets of stored social media data could be used to generate semantic analysis about a particular topic, brand, company or person.
Apparently, I lack the very gene that every Forrester, Gartner and the like analyst has - to arrive at catchy but thoroughly generic terms to describe the latest and greatest trends in technologies, myself preferring to find understanding through doing and the pragmatic application of such things.
Luckily, working for VANTIQ, I have been face-to-face on a daily basis with many of these pragmatic applications of what we are calling digital transformation. Let me share a few with you by Industry, and perhaps through these descriptions, a material definition of this phrase will emerge at the end.
- Industry 4.0: Another one of these vague innocuous phrases that could mean anything, and if you are starting to think we have a Russian doll situation starting here, you're probably not wrong - but let me share my experience in this field here. Dusty old manufacturing companies are reinventing themselves using technology to enhance their business practices in a lot of different ways. A significant one is Internet of Things (IoT) sensors applied to manufacturing equipment to monitor and predict the operation of these big expensive machines. Sensors are finding their way into the factory floor in a big way on assembly lines, using cameras to add additional security and safety capabilities. Of course, IoT is just a small part of the overall Industry 4.0 which attempts to impact every part of the business with smarter, more connected systems, but let's use IoT here as the one, big, easily identifiable thing we can use to describe digital transformation.
- Supply Chain: This is a field that impacts many different verticals, but my experience has been limited to companies that are looking to gather new insights and new information from the fluid, chaotic, ever shifting world of incoming and outgoing materials we call supply chain. One such case is using a suite of free or pay-per-use APIs to generate a world-wide threat analysis for a given supplier. This type of system was meant to provide real-time insights into supply chain threats by analyzing everything from weather, terrorist threats, forest fires, viral outbreaks and political instability to instantly identify threats to the inbound raw materials. These threats - if not abated or avoided - would of course have direct though perhaps not immediate impact on the downstream delivery of products. The result was an interesting use of currently available APIs to create new useful insights that can have a positive impact on an OEM.
- Field Service Management: This is the last one I will cover but I am going to mention a lot of technologies. In this example, I was involved in a project to create an Uber style system to locate 3rd party field service technicians based on proximity to a customer site and a skillset. To enhance the technician's experience working with the hardware, we can connect with multiple smart systems to provide, for example, contextual knowledge base information or utilize augmented reality systems. This allows the field tech to better perform her job both faster and with less chance of failure when troubleshooting a piece of IT equipment. The Uber aspect of identifying, accepting, and dispatching is fully automated. This is a system that - much like Uber - can run on its own without human operators monitoring the dispatch requests while still being able to pull up the current progress of a technician's installation or repair at any time. Additionally, analytics are used to determine how the techs are performing, what types of hardware or situations present the greatest challenges or the fewest, and these insights can be used to improve a technician's skillset with training in specific areas or incentivizing the technician with performance benefits based on the data sets. Who knows what new insights this type of data analysis might discover?
Let's recap: we have covered IoT, APIs, connected smart systems, analytics, and automation in this quest to identify what it really means to digitally transform. If we squish all these together and try to take a high level view combined with an aesthetically pleasing phrasing, I think we can safely say that Digital Transformation is the attempt by any organization to use technology to make smarter, faster decisions for the business in the hopes that smarter and faster (dare we say 'real-time') businesses are more successful than slower and less smart ones - and therefore more likely to succeed.
There you have it: the ideal description of digital transformation from a technology pragmatist!
Patrick Burma is a Sr. Solutions Engineer at VANTIQ where he spends his days helping companies create real-world solutions to digitally transform themselves. Please add your comments below and Subscribe to the Blog to receive notifications of future blog posts.